Bar Charts

%matplotlib notebook

import matplotlib.pyplot as plt
import numpy as np

linear_data = np.array([1,2,3,4,5,6,7,8])
exponential_data = linear_data**2

plt.figure()

xvals = range(8)
plt.bar(xvals, 
        linear_data, 
        width = 0.3, 
        color='blue');

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In order to make room for a side-by-side bar chart, for each original x-value, add a constant amount of space. Alignment of x-axis labels is one of the more cumbersome aspects of matplotlib.

Further, adding dates as x-axis labels must be completed manually. And, there is not an obvious way to plot several series of data in groups across time, for example.

new_xvals = []

for item in xvals:
    new_xvals.append(item+0.3)

plt.bar(new_xvals, 
        exponential_data, 
        width = 0.3, 
        color='red');

Error bars can be added to the y-axis.

plt.figure()

from random import randint

linear_err = [randint(0,5) for x in range(len(linear_data))]
plt.bar(xvals, 
        linear_data, 
        width = 0.3, 
        color='orange', 
        yerr=linear_err);

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Stacked bar charts can be made by specifying the bottom attributes.

plt.figure()
xvals = range(len(linear_data))
plt.bar(xvals, 
        linear_data, 
        width = 0.3, 
        color='b')
plt.bar(xvals, 
        exponential_data, 
        width = 0.3, 
        bottom=linear_data, 
        color='r');

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Finally, horizontal bar charts can be made using barh instead of bar. Note that what had been the width parameter becomes the height parameter, and bottom becomes left.

plt.figure()
xvals = range(8)
plt.barh(xvals, 
         linear_data, 
         height = 0.3, 
         color='b')
plt.barh(xvals, 
         exponential_data, 
         height = 0.3, 
         left=linear_data, 
         color='r');

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